Instructions to use gafiatulin/vibevoice-7b-coreai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- VibeVoice
How to use gafiatulin/vibevoice-7b-coreai with VibeVoice:
import torch, soundfile as sf, librosa, numpy as np from vibevoice.processor.vibevoice_processor import VibeVoiceProcessor from vibevoice.modular.modeling_vibevoice_inference import VibeVoiceForConditionalGenerationInference # Load voice sample (should be 24kHz mono) voice, sr = sf.read("path/to/voice_sample.wav") if voice.ndim > 1: voice = voice.mean(axis=1) if sr != 24000: voice = librosa.resample(voice, sr, 24000) processor = VibeVoiceProcessor.from_pretrained("gafiatulin/vibevoice-7b-coreai") model = VibeVoiceForConditionalGenerationInference.from_pretrained( "gafiatulin/vibevoice-7b-coreai", torch_dtype=torch.bfloat16 ).to("cuda").eval() model.set_ddpm_inference_steps(5) inputs = processor(text=["Speaker 0: Hello!\nSpeaker 1: Hi there!"], voice_samples=[[voice]], return_tensors="pt") audio = model.generate(**inputs, cfg_scale=1.3, tokenizer=processor.tokenizer).speech_outputs[0] sf.write("output.wav", audio.cpu().numpy().squeeze(), 24000) - Notebooks
- Google Colab
- Kaggle
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README.md
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- on-device
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- m4-max
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- text-to-speech
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---
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# VibeVoice 7B — multi-speaker TTS (Core AI)
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**On-device performance (M4 Max, Core AI):** 2.37× RTF
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> ⚠️ **Beta artifacts.** These `.aimodel` bundles are compiled for macOS 27 / Xcode 27 beta (Core AI). They may need re-export on the GA toolchain. The original weights are Microsoft VibeVoice (see upstream for the model license).
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"decode_compute": "gpu",
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"sem_compute": "gpu"
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```
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- on-device
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- m4-max
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base_model:
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- vibevoice/VibeVoice-7B
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---
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# VibeVoice 7B — multi-speaker TTS (Core AI)
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High-quality multi-speaker TTS, 7B Qwen2 backbone. cfg 2.0 fused sampler avoids long-form static buildup.
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**On-device performance (M4 Max, Core AI):** 2.37× RTF.
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> ⚠️ **Beta artifacts.** These `.aimodel` bundles are compiled for macOS 27 / Xcode 27 beta (Core AI). They may need re-export on the GA toolchain. The original weights are Microsoft VibeVoice (see upstream for the model license).
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"decode_compute": "gpu",
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"sem_compute": "gpu"
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}
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```
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